IDEAS home Printed from https://ideas.repec.org/a/eee/finlet/v56y2023ics1544612323004816.html
   My bibliography  Save this article

Information shocks and investor underreaction: Evidence from the Bitcoin market

Author

Listed:
  • Meng, Yongqiang
  • Goodell, John W.
  • Shen, Dehua

Abstract

Despite research showing investor attention is especially impacting on Bitcoin, strangely, there is little research focusing on Bitcoin regarding market reactions to information shocks. Employing jumps as a proxy for information shocks, results show significantly more positive daily jump returns than negative daily jump returns. Results also show that Bitcoin investors underreact to large information shocks. Mechanism analysis shows that investor attention reduces the magnitude of underreaction.

Suggested Citation

  • Meng, Yongqiang & Goodell, John W. & Shen, Dehua, 2023. "Information shocks and investor underreaction: Evidence from the Bitcoin market," Finance Research Letters, Elsevier, vol. 56(C).
    • Handle: RePEc:eee:finlet:v:56:y:2023:i:c:s1544612323004816
    DOI: 10.1016/j.frl.2023.104109
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1544612323004816
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.frl.2023.104109?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. S. James Press, 1967. "A Compound Events Model for Security Prices," The Journal of Business, University of Chicago Press, vol. 40, pages 317-317.
    2. Bernard, Vl & Thomas, Jk, 1989. "Post-Earnings-Announcement Drift - Delayed Price Response Or Risk Premium," Journal of Accounting Research, Wiley Blackwell, vol. 27, pages 1-36.
    3. Savor, Pavel G., 2012. "Stock returns after major price shocks: The impact of information," Journal of Financial Economics, Elsevier, vol. 106(3), pages 635-659.
    4. Jia, Boxiang & Shen, Dehua & Zhang, Wei, 2022. "Extreme sentiment and herding: Evidence from the cryptocurrency market," Research in International Business and Finance, Elsevier, vol. 63(C).
    5. Jiang, Christine X. & Likitapiwat, Tanakorn & McInish, Thomas H., 2012. "Information Content of Earnings Announcements: Evidence from After-Hours Trading," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 47(6), pages 1303-1330, December.
    6. Fama, Eugene F, 1991. "Efficient Capital Markets: II," Journal of Finance, American Finance Association, vol. 46(5), pages 1575-1617, December.
    7. Paul C. Tetlock, 2010. "Does Public Financial News Resolve Asymmetric Information?," Review of Financial Studies, Society for Financial Studies, vol. 23(9), pages 3520-3557.
    8. Shen, Dehua & Urquhart, Andrew & Wang, Pengfei, 2019. "Does twitter predict Bitcoin?," Economics Letters, Elsevier, vol. 174(C), pages 118-122.
    9. Li, Yue & Goodell, John W. & Shen, Dehua, 2021. "Comparing search-engine and social-media attentions in finance research: Evidence from cryptocurrencies," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 723-746.
    10. Ball, R & Brown, P, 1968. "Empirical Evaluation Of Accounting Income Numbers," Journal of Accounting Research, Wiley Blackwell, vol. 6(2), pages 159-178.
    11. S. P. Kothari & Susan Shu & Peter D. Wysocki, 2009. "Do Managers Withhold Bad News?," Journal of Accounting Research, Wiley Blackwell, vol. 47(1), pages 241-276, March.
    12. Jacob Boudoukh & Ronen Feldman & Shimon Kogan & Matthew Richardson, 2019. "Information, Trading, and Volatility: Evidence from Firm-Specific News," Review of Financial Studies, Society for Financial Studies, vol. 32(3), pages 992-1033.
    13. Peter Kelly, 2018. "The Information Content of Realized Losses," Review of Financial Studies, Society for Financial Studies, vol. 31(7), pages 2468-2498.
    14. Jiang, George J. & Zhu, Kevin X., 2017. "Information Shocks and Short-Term Market Underreaction," Journal of Financial Economics, Elsevier, vol. 124(1), pages 43-64.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaoping Li & Zhipeng Zhang & Junyu Pan & Jihong Duan, 2023. "Investor attention and the predictability of the volatility of CNY‐CNH spreads: Evidence from a GARCH‐MIDAS model," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(5), pages 4939-4959, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Jiang, George J. & Zhu, Kevin X., 2017. "Information Shocks and Short-Term Market Underreaction," Journal of Financial Economics, Elsevier, vol. 124(1), pages 43-64.
    2. Wang, Qingxia & Faff, Robert & Zhu, Min, 2022. "Realized moments and the cross-sectional stock returns around earnings announcements," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 408-427.
    3. Mohrschladt, Hannes & Langer, Thomas, 2020. "Biased information weight processing in stock markets," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 89-106.
    4. S. P. Kothari & Charles Wasley, 2019. "Commemorating the 50‐Year Anniversary of Ball and Brown (1968): The Evolution of Capital Market Research over the Past 50 Years," Journal of Accounting Research, Wiley Blackwell, vol. 57(5), pages 1117-1159, December.
    5. Jiang, Hao & Li, Sophia Zhengzi & Wang, Hao, 2021. "Pervasive underreaction: Evidence from high-frequency data," Journal of Financial Economics, Elsevier, vol. 141(2), pages 573-599.
    6. Fernando Rubio, 2005. "Estrategias Cuantitativas De Valor Y Retornos Por Accion De Largo," Finance 0503029, University Library of Munich, Germany.
    7. Lu Zhang, 2019. "Q-factors and Investment CAPM," NBER Working Papers 26538, National Bureau of Economic Research, Inc.
    8. Erica X. N. Li & Dmitry Livdan & Lu Zhang, 2009. "Anomalies," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4301-4334, November.
    9. Daniel, Kent & Hirshleifer, David & Teoh, Siew Hong, 2002. "Investor psychology in capital markets: evidence and policy implications," Journal of Monetary Economics, Elsevier, vol. 49(1), pages 139-209, January.
    10. Baars, Maren & Mohrschladt, Hannes, 2021. "An alternative behavioral explanation for the MAX effect," Journal of Economic Behavior & Organization, Elsevier, vol. 191(C), pages 868-886.
    11. Wu, Chen-Hui, 2022. "The informativeness of brokerage reports: Privately-circulated versus publicly-disseminated news," International Review of Financial Analysis, Elsevier, vol. 83(C).
    12. Amir, Eli & Lev, Baruch, 1996. "Value-relevance of nonfinancial information: The wireless communications industry," Journal of Accounting and Economics, Elsevier, vol. 22(1-3), pages 3-30, October.
    13. DeLisle, R. Jared & Ferguson, Michael F. & Kassa, Haimanot & Zaynutdinova, Gulnara R., 2021. "Hazard stocks and expected returns," Journal of Banking & Finance, Elsevier, vol. 125(C).
    14. Chu, Gang & Dowling, Michael & Shen, Dehua & Zhang, Yongjie, 2023. "Information demand density matters: Evidence from the post-earnings announcement drift," International Review of Financial Analysis, Elsevier, vol. 86(C).
    15. Rácz, Dávid Andor & Huszár, Gergely, 2019. "The Effects of Earnings Surprises in Quarterly Reports on S&P 500 Components," Public Finance Quarterly, Corvinus University of Budapest, vol. 64(2), pages 239-259.
    16. Fernando Rubio, 2005. "Eficiencia De Mercado, Administracion De Carteras De Fondos Y Behavioural Finance," Finance 0503028, University Library of Munich, Germany, revised 23 Jul 2005.
    17. Julio A. Crego, 2017. "Does Public News Decrease Information Asymmetries? Evidence from the Weekly Petroleum Status Report," Working Papers wp2017_1714, CEMFI.
    18. Victor Bernard & Jacob Thomas & James Wahlen, 1997. "Accounting†Based Stock Price Anomalies: Separating Market Inefficiencies from Risk," Contemporary Accounting Research, John Wiley & Sons, vol. 14(2), pages 89-136, June.
    19. Sarfraz A. Khan & Gerald Lobo & Emeka T. Nwaeze, 2017. "Public re-release of going-concern opinions and market reaction," Accounting and Business Research, Taylor & Francis Journals, vol. 47(3), pages 237-267, April.
    20. Bai, Min & Qin, Yafeng & Zhang, Huiping, 2021. "Stock price crashes in emerging markets," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 466-482.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:finlet:v:56:y:2023:i:c:s1544612323004816. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/frl .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.